矩阵方程AXB=D的最小二乘Hermite解及其加权最佳逼近

本中,我们讨论了矩阵方程AXB=D的最小二乘Hermite解,通过运用广义奇异值分解(GSVD)，获得了解的通式。此外,对于给定矩阵F，也得到了它的加权最佳逼近表达式。     

A new algorithm for fixed design regression and denoising

In this paper, we present a new algorithm to estimate a regression function in a fixed design regression model, by piecewise (standard and trigonometric) polynomials computed with an automatic choice of the knots of the subdivision and of the degrees of the polynomials on each sub-interval. First we give the theoretical background underlying the method: the theoretical performances of our penalized least-squares estimator are based on non-asymptotic evaluations of a mean-square type risk. Then we explain how the algorithm is built and possibly accelerated (to face the case when the number of observations is great), how the penalty term is chosen and why it contains some constants requiring an empirical calibration. Lastly, a comparison with some well-known or recent wavelet methods is made: this brings out that our algorithm behaves in a very competitive way in term of denoising and of compression.     

Polyparametric modification equation for estimating thermodynamic properties of energetic nitro compounds

Calculation methods, based on hybrid density-functional theory with the basis sets of B3LYP/ 6-311+G (2d, p)//B3LYP/6-31G(d, p)and B3LYP/6-31+G(d)//B3LYP/6-31G(d, p), were applied to determine the thermodynamic characteristics of various energetic nitro compounds. A parametric modification equation and the least-squares approach were used to identify 21 of the energetic research compounds. The atomization energies of these 21 compounds have an average relative error of 0.21–0.25% of the experimental values. The enthalpy (H _f) and the Gibbs energy (G _f) of formation have mean absolute errors of 10.8–11.4 kJ/ mol (2.6–2.7 kcal/mol) and 10.0–10.3 kJ/mol (2.4 kcal/ mol), respectively. The enthalpy and the Gibbs energy of formation obtained exceed those in the literature obtained by semiempirical calculations. The calibrated least-squares parameters and parametric equations were used to predict H _f and G _f for the five newly developed energetic nitro compounds for further applications.Acknowledgements. The authors would like to thank the National Science Council of the Republic of China for financial support of this work under grant no. NSC-91-2113-M-014-003. The National Center for High-Performance Computing providing the computation facility is also acknowledged.     

Inside the Solvency 2 Black Box: Net Asset Values and Solvency Capital Requirements with a least-squares Monte-Carlo approach

The calculation of Net Asset Values and Solvency Capital Requirements in a Solvency 2 context–and the derivation of sensitivity analyses with respect to the main financial and actuarial risk drivers–is a complex procedure at the level of a real company, where it is illusory to be able to rely on closed-form formulas. The most general approach to performing these computations is that of nested simulations. However, this method is also hardly realistic because of its huge computation resources demand. The least-squares Monte Carlo method has recently been suggested as a way to overcome these difficulties. The present paper confirms that using this method is indeed relevant for Solvency 2 computations at the level of a company.     

The numerical solution of the acoustic wave scattering from penetrable obstacles by a least-squares method

This paper documents a numerical method for a two dimensional time-harmonic wave scattering problem by penetrable obstacles. The Fourier–Bessel function combining a multipole expansion is used to give an approximation of the scattering field. This method is based on the least-squares technique. Especially, we find a simple function to control the errors, and then give the theoretical results of the presented method. The continuity across the element boundaries is enforced by minimizing a simple quadratic functional. This method does not need to truncate the domain and could obtain high accuracy by increasing the number of basis functions with even coarse mesh. At last, we give some examples to illustrate the effectiveness of the approach including the solution domain being multiple or even multi-connected.     

速率光纤陀螺寻北仪倾斜补偿算法研究

针对速率光纤陀螺寻北仪,提出了一种倾斜补偿算法.通过采用积分滑动和最小二乘拟合滤波技术,对光纤陀螺和加速度计原始测量信号进行数据处理.试验数据表明,采用本算法解决了由倾斜角存在影响其寻北准确度的关键技术问题.同时给出了提高光纤陀螺寻北仪的准确度的可能因素.     

Short-wave near-infrared spectroscopy analysis of major compounds in milk powder and wavelength assignment

In this study, short-wave near-infrared (NIR) spectroscopy at 800–1050 nm region was investigated for the analysis of main compounds in milk powder. Through quantitative analysis, the feasibility is further demonstrated for the simultaneous measurement of fat, proteins and carbohydrate in milk powder. Two models, partial least-squares and least-squares support vector machine, were compared and utilized for regression coefficients and loading weights. The affect of standard normal variate spectral pretreatment to model performance was evaluated. Based on the resulted coefficients and loading weights, interesting wavelength regions of nutrition in milk powder are screened and the assignment of all specific wavelengths is firstly proposed in the details associated with chemical base. Instead of the whole short-wave NIR spectral data, these assigned wavelengths which can be reliably exploited were used for the content determination. Compared with other spectroscopy technique, assigned short-wave NIR spectral wavelengths did a good work. Determination coefficients for prediction are 0.981, 0.984, and 0.982, respectively for three components. The proposed wavelength assignment in the short-wave NIR region could be used for the component contents determination of milk powder, and could be as a guidance to interpret the spectra of milk powder.     

Analysis of least-squares mixed finite element methods for nonlinear nonstationary convection-diffusion problems

Some least-squares mixed finite element methods for convection-diffusion problems, steady or nonstationary, are formulated, and convergence of these schemes is analyzed. The main results are that a new optimal a priori error estimate of a least-squares mixed finite element method for a steady convection-diffusion problem is developed and that four fully-discrete least-squares mixed finite element schemes for an initial-boundary value problem of a nonlinear nonstationary convection-diffusion equation are formulated. Also, some systematic theories on convergence of these schemes are established.

     

Bootstrap tests for unit roots in seasonal autoregressive models

This paper proposes bootstrap tests for the presence of unit roots in a seasonal autoregressive model. The asymptotic validity of the proposed bootstrap scheme is established, and Monte Carlo experiments are used to investigate the small-sample performance of the tests.     

Adaptive finite element methods for the identification of distributed parameters in elliptic equation

In this paper, adaptive finite element method is developed for the estimation of distributed parameter in elliptic equation. Both upper and lower error bound are derived and used to improve the accuracy by appropriate mesh refinement. An efficient preconditioned project gradient algorithm is employed to solve the nonlinear least-squares problem arising in the context of parameter identification problem. The efficiency of our error estimators is demonstrated by some numerical experiments.